What you can do with AI at the edge

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The Intelligence that Makes Smart Homes Smart

Much of the convenience and security that Smart Homes have claimed to promise has yet to become a reality. To understand why, consider that the technology behind a Smart Home historically required significant CPU power combined with a GPU or…
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Take Video Conferencing to the Next Level with AI Image Segmentation

Andrew, one of Xnor.ai's engineers, showing a demo of Image Segmentation running off a webcam video feed, using 60 MB of memory and just the CPU - no GPU necessary. With so many meetings involving participants from multiple locations, it’s…
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Real-Time Image Segmentation for Mobile, Retail and Videoconferencing

Imagine being able to create more focus in your video-conference, or transport users to a different world in a mobile app experience. Image segmentation, a computer vision machine learning task, makes this a reality by creating pixel-accurate…
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Xnor.ai and Toradex at Arm TechCon 2018

Today we’re featuring Toradex, one of our hardware partners who will be exhibiting at Arm TechCon this week in San Jose, California. If you’re at the conference, come visit booth #1134 to see a joint demonstration of Xnor running on…
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Improving deep learning accuracy at the edge

More refined labels at training yield higher accuracy for on-device models Hessam Bagherinezhad, Maxwell Horton, Mohammad Rastegari, Ali Farhadi Advancements in deep learning opened the possibility for any camera to operate as a smart sensor…
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AI At the Edge On a Raspberry Pi Zero

At Xnor.ai we work on every aspect of computing platforms to optimize artificial intelligence and machine learning, from the software down to the hardware. We have a diverse set of skills, so it is easy to quickly build a prototype…